Multiresolution mapping and informative path planning for UAV-based terrain monitoring

Popović, Marija; Vidal-Calleja, Teresa; Hitz, Gregory; Sa, Inkyu; Siegwart, Roland; Nieto, Juan

doi:10.1109/iros.2017.8202317

Cited by 58 publications

(68 citation statements)

References 23 publications

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“…The former performs online replanning while the latter executes an a priori path. Myopic methods [11] differ from non-myopic ones [3] in terms of their planning look-ahead. The former navigates greedily by selecting next-best views, while the latter plans with a finite lookahead to escape local minima.…”

Section: Related Workmentioning

confidence: 99%

“…The former navigates greedily by selecting next-best views, while the latter plans with a finite lookahead to escape local minima. Finally, whereas discrete strategies [10,12] perform combinatorial optimization on pre-defined grids, continuous solvers [3,13,14] operate directly in the robot workspace to achieve better scalability.…”

Section: Related Workmentioning

confidence: 99%

“…Our algorithm is adaptive, non-myopic, and continuous. It falls into a recently emerged category of methods which optimize a smooth continuous trajectory for maximal information gain [3,9,14,15]. Specifically, we build upon the work of Popović et al [3] by introducing a new adaptive planning scheme based on BO [15] to perform exploration while focusing on potential targets as they are detected.…”

Section: Related Workmentioning

confidence: 99%

“…Our field mapping strategy is based on the approach of Popović et al [3], allowing us to incorporate probabilistic sensor models for data fusion with constant-time measurement updates. We represent the monitored ground field of target occupancy using a GP model, which captures spatial correlations in a probabilistic and non-parametric way [19].…”

Section: B Field Modeling and Mappingmentioning

confidence: 99%

“…Autonomous target search in cluttered environments is a challenging problem relevant for a wide range of applications, e.g., finding victims in SaR operations [1,2], monitoring vegetation in precision agriculture [3,4], patrolling military borders [5], and tracking endangered species [6]. With recent technological advances, UAVs are rapidly gaining popularity as a aerial data acquisition tool for this task.…”

Section: Introductionmentioning

confidence: 99%

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Obstacle-aware Adaptive Informative Path Planning for UAV-based Target Search

Meera

Popović

Millane

et al. 2019

2019 International Conference on Robotics and Automation (ICRA)

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Target search with unmanned aerial vehicles (UAVs) is relevant problem to many scenarios, e.g., search and rescue (SaR). However, a key challenge is planning paths for maximal search efficiency given flight time constraints. To address this, we propose the Obstacle-aware Adaptive Informative Path Planning (OA-IPP) algorithm for target search in cluttered environments using UAVs. Our approach leverages a layered planning strategy using a Gaussian Process (GP)based model of target occupancy to generate informative paths in continuous 3D space. Within this framework, we introduce an adaptive replanning scheme which allows us to trade off between information gain, field coverage, sensor performance, and collision avoidance for efficient target detection. Extensive simulations show that our OA-IPP method performs better than state-of-the-art planners, and we demonstrate its application in a realistic urban SaR scenario.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: B Field Modeling and Mappingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Obstacle-aware Adaptive Informative Path Planning for UAV-based Target Search

Meera

Popović

Millane

et al. 2019

2019 International Conference on Robotics and Automation (ICRA)

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Routing and collision avoidance techniques for unmanned aerial vehicles: Analysis, optimal solutions, and future directions

Sharma

Obaidat

Sharma

et al. 2020

Int J Communication

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SummaryRouting remains the most important problem to be explored, for discovering an ideal pathway in unmanned aerial vehicles (UAVs). Several problems for identifying and targeting location continue giving the immense motility of UAVs. In routing planning, optimum decisions have to be taken for several vital operations for solving the issues in UAVs. Many types of routing techniques of UAVs, which have been used for many years, have been analyzed in this paper. Routing techniques aim to provide striking‐free surroundings to the UAVs and not only to find an optimum path but also the smallest path. Routing techniques play a vital part in the development of a secured way in a minimal time to reach the ultimate destination and hence much needed. There are various routing techniques, real‐time applications of UAVs which are elaborated in this paper, namely, representative, cooperative, and noncooperative techniques. In UAV, collision avoidance is very important for the obstacle‐free environment. Collision avoidance techniques are discussed for a safe environment of UAV. Further, the UAVs network communication coverage and connectivity by these techniques are discussed. Finally, we discuss the security and connectivity and future directions in UAV.

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Kriging‐based robotic exploration for soil moisture mapping using a cosmic‐ray sensor

Fentanes

Badiee

Duckett

et al. 2019

Journal of Field Robotics

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Soil moisture monitoring is a fundamental process to enhance agricultural outcomes and to protect the environment. The traditional methods for measuring moisture content in the soil are laborious and expensive, and therefore there is a growing interest in developing sensors and technologies which can reduce the effort and costs. In this work, we propose to use an autonomous mobile robot equipped with a state‐of‐the‐art noncontact soil moisture sensor building moisture maps on the fly and automatically selecting the most optimal sampling locations. We introduce an autonomous exploration strategy driven by the quality of the soil moisture model indicating areas of the field where the information is less precise. The sensor model follows the Poisson distribution and we demonstrate how to integrate such measurements into the kriging framework. We also investigate a range of different exploration strategies and assess their usefulness through a set of evaluation experiments based on real soil moisture data collected from two different fields. We demonstrate the benefits of using the adaptive measurement interval and adaptive sampling strategies for building better quality soil moisture models. The presented method is general and can be applied to other scenarios where the measured phenomena directly affect the acquisition time and need to be spatially mapped.

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Multiresolution mapping and informative path planning for UAV-based terrain monitoring

Cited by 58 publications

References 23 publications

Obstacle-aware Adaptive Informative Path Planning for UAV-based Target Search

Obstacle-aware Adaptive Informative Path Planning for UAV-based Target Search

Routing and collision avoidance techniques for unmanned aerial vehicles: Analysis, optimal solutions, and future directions

Kriging‐based robotic exploration for soil moisture mapping using a cosmic‐ray sensor

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